The applicant is a clinical neuropsychologist whose long-term career goal is to become an independent researcher conducting work in the translational neuroscience of late life depression (LLD) using neuropsychological and neuroimaging tools. Individuals with LLD are thought to encompass a neurobiologically heterogeneous group. Previous studies with small samples and mixed etiologies of LLD subjects have been limited in their development of knowledge of the basis of the disorder and of sub-phenotypes, but have been important in taking first steps toward difficult goals. For example, individuals with LLD present with high rates of treatment resistance to typical antidepressant regimens, increased vulnerability to decline in cognition and function, and high rates of treatment non-adherence. Some initial efforts have been made to identify more accurate intermediate endophenotypes (IE) of individuals with LLD, which might improve prediction of who is most likely to display cognitive and functional decline and identify individuals most likely to respond to specific treatment regimens. To date, research on LLD has focused primary on executive functioning deficits, related to disruption of dorsolateral-striatal circuitry using small samples. Observations of executive functioning deficits and associated disruption to dorsolateral-striatal pathways among patients with LLD have been predictive of poor psychiatric outcomes, such as treatment resistance. In addition, there has been less investigation into the ability of baseline neuropsychological and neuroimaging measures to predict the course of broad cognitive and functional decline, despite the fact that prediction is precisely what clinicians and families might find most useful in planning and care. Furthermore, clinical measures such as apathy and the potential predictive validity of such measures in related neural circuitry, is as yet unknown. Establishing which neuropsychological and clinical measures are related to the neural circuitry underlying LLD can be of signal value toward developing treatment to protect and enhance the respective underlying neural circuits. Furthermore, if these measures and circuits are predictive of course and change in broad cognitive areas, clinical features, and everyday functioning, this knowledge could more readily be transferred to clinical care practices. Thus, the primary objective of this study is to probe two neural circuits implicated in the etiology of LLD. To achieve this objective, the candidate proposes to distinguish neural circuitry related to executive dysfunction (as defined by comprehensive baseline neuropsychological assessment) from circuitry related to symptoms of apathy using resting state functioning connectivity (rRSfC, a functional MRI technique that examines neural connectivity of brain regions during a resting state), as well as diffusion tensor imaging as a microstructural compliment. Furthermore, the project is designed as a longitudinal, predictive study. It uses neuropsychological, clinical, and neural circuitry measures to map and predict course of LLD, including changes in cognitive areas, clinical features, and everyday functioning. It is designed so that cognitive and behavioral features of LLD that predict decline can be effectively evaluated and easily translated into clinic settings. Participants will include 40 individuals with LLD, antidepressant-free at baseline, relative to 20 controls. The two groups will be matched for age, gender, education, and medical comorbidities. They will be re-assessed at one- and two-year follow-up visits with a neuropsychological battery, including symptom and behavioral measures, to better understand the extent to which baseline neuropsychological alterations can predict the course of cognition and function among individuals with LLD. Linking neurobiological circuitry with neuropsychological and behavioral measures will allow for the mechanistic definition of simplified, non-imaging measures, anchored on a background of neurobiological correlates that may predict the course of cognition and function of LLD, leading to more accurate assessments, the specification of more valid phenotypes in this complex illness, and a better targeting of preventive and treatment strategies.